Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	15,011
2	New Jersey	12,518
3	Massachusetts	8,191
4	Connecticut	7,291
5	Rhode Island	7,276
6	Louisiana	5,822
7	District of Columbia	5,514
8	Delaware	4,274
9	Michigan	3,824
10	Illinois	3,620
11	Pennsylvania	3,373
12	Maryland	3,223
13	South Dakota	2,538
14	Colorado	2,397
15	Indiana	2,370
16	Georgia	2,187
17	Mississippi	2,047
18	Iowa	1,859
19	Washington	1,820
20	Nebraska	1,802
21	Virginia	1,585
22	Nevada	1,528
23	Florida	1,495
24	Tennessee	1,434
25	New Hampshire	1,425
26	Ohio	1,396
27	Vermont	1,370
28	New Mexico	1,347
29	Alabama	1,333
30	Utah	1,321
31	North Dakota	1,236
32	Missouri	1,168
33	Kansas	1,164
34	California	1,143
35	South Carolina	1,090
36	Wisconsin	1,044
37	Arkansas	1,016
38	Idaho	998
39	Kentucky	927
40	Arizona	922
41	Texas	895
42	North Carolina	871
43	Oklahoma	828
44	Maine	761
45	Minnesota	676
46	Wyoming	672
47	West Virginia	600
48	Oregon	558
49	Alaska	468
50	Puerto Rico	434
51	Hawaii	423
52	Montana	420

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	New York	349
2	New Jersey	337
3	Rhode Island	317
4	Massachusetts	265
5	Delaware	246
6	Connecticut	194
7	Nebraska	174
8	District of Columbia	171
9	Illinois	163
10	Maryland	158
11	Iowa	148
12	Indiana	112
13	Colorado	89
14	North Dakota	84
15	South Dakota	77
16	Pennsylvania	75
17	Virginia	75
18	Mississippi	73
19	Louisiana	66
20	Kansas	64
21	Tennessee	54
22	New Hampshire	53
23	Michigan	52
24	Georgia	51
25	New Mexico	47
26	Utah	47
27	Wisconsin	41
28	Minnesota	37
29	South Carolina	35
30	Alabama	34
31	North Carolina	34
32	Nevada	33
33	California	32
34	Ohio	32
35	Washington	32
36	Arizona	30
37	Missouri	29
38	Arkansas	28
39	Kentucky	27
40	Texas	26
41	Florida	24
42	Wyoming	23
43	Maine	14
44	Vermont	14
45	Oklahoma	13
46	Oregon	13
47	West Virginia	12
48	Puerto Rico	11
49	Idaho	6
50	Alaska	2
51	Hawaii	1
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	889
2	New Jersey	680
3	Connecticut	564
4	Massachusetts	435
5	Louisiana	365
6	Michigan	341
7	District of Columbia	262
8	Rhode Island	219
9	Illinois	157
10	Pennsylvania	152
11	Maryland	141
12	Delaware	128
13	Indiana	125
14	Colorado	122
15	Washington	101
16	Georgia	92
17	Mississippi	76
18	Vermont	75
19	Nevada	71
20	Ohio	64
21	Virginia	53
22	Florida	50
23	Minnesota	50
24	New Mexico	49
25	Oklahoma	49
26	Kentucky	48
27	Missouri	48
28	Wisconsin	48
29	Alabama	46
30	California	45
31	New Hampshire	44
32	Kansas	43
33	Iowa	40
34	Arizona	38
35	Maine	37
36	South Carolina	34
37	Idaho	32
38	North Carolina	31
39	Nebraska	28
40	Tennessee	28
41	North Dakota	24
42	Texas	24
43	Oregon	21
44	West Virginia	20
45	Arkansas	16
46	Puerto Rico	16
47	Montana	13
48	South Dakota	12
49	Utah	12
50	Wyoming	12
51	Hawaii	11
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Connecticut	23
2	Massachusetts	21
3	New York	19
4	New Jersey	16
5	District of Columbia	15
6	Michigan	10
7	Rhode Island	9
8	Delaware	8
9	Maryland	7
10	Louisiana	6
11	Indiana	5
12	Illinois	4
13	Pennsylvania	4
14	Minnesota	3
15	New Mexico	3
16	Georgia	2
17	Iowa	2
18	Mississippi	2
19	Alabama	1
20	California	1
21	Colorado	1
22	Kansas	1
23	Missouri	1
24	Nevada	1
25	New Hampshire	1
26	North Carolina	1
27	North Dakota	1
28	Ohio	1
29	South Carolina	1
30	Vermont	1
31	Virginia	1
32	Washington	1
33	Wisconsin	1
34	Alaska	0
35	Arizona	0
36	Arkansas	0
37	Florida	0
38	Hawaii	0
39	Idaho	0
40	Kentucky	0
41	Maine	0
42	Montana	0
43	Nebraska	0
44	Oklahoma	0
45	Oregon	0
46	Puerto Rico	0
47	South Dakota	0
48	Tennessee	0
49	Texas	0
50	Utah	0
51	West Virginia	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	98,544	1	99
Lincoln	Arkansas	57,893	2	99
Bledsoe	Tennessee	39,033	3	99
Rockland	New York	34,888	4	99
Marion	Ohio	33,613	5	99
Davidson	Tennessee	3,584	205	93
Richland	South Carolina	2,020	444	85
Pierce	Washington	1,497	622	80
Orange	California	669	1265	59
York	South Carolina	662	1275	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,280	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	2,110	3	99
Nassau	New York	1,476	4	99
Early	Georgia	1,472	5	99
Pierce	Washington	54	665	78
Richland	South Carolina	46	761	75
Davidson	Tennessee	36	872	72
Orange	California	13	1244	60
York	South Carolina	11	1275	59

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.